Unconventional monetary policy in a nonlinear quadratic model

IF 0.7 4区 经济学 Q3 ECONOMICS Studies in Nonlinear Dynamics and Econometrics Pub Date : 2020-09-18 DOI:10.1515/snde-2019-0099
T. Faulwasser, M. Gross, W. Semmler, Prakash Loungani
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引用次数: 9

Abstract

Abstract After the financial market meltdown and the Great Recession of the years 2007–9, the financial market-macro link has become an important issue in monetary policy modeling. We develop a dynamic model that contains a nonlinear Phillips curve, a dynamic output equation, and a nonlinear credit flow equation – capturing the importance of credit cycles, risk premia, and credit spreads. Our Nonlinear Quadratic Model (NLQ) model has three dynamic state equations and a quadratic objective function. It can be used to evaluate the response of central banks to the Great Recession in moving from conventional to unconventional monetary policy. We solve the model with a new numerical procedure using estimated parameters for the euro area. We conduct simulations to explore the (de)stabilizing effects of the nonlinearities in the model. We demonstrate that credit flows, risk premia, and credit spreads play an important role as an amplification mechanism and in affecting the transmission of monetary policy. We thereby highlight the importance of the natural rate of interest as an anchor for a central bank target and the weight it places on the credit flows for the effectiveness of unconventional monetary policy. Our model is similar in structure compared to larger scale macro-econometric models which many central banks employ.
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非线性二次模型下的非常规货币政策
摘要在金融市场崩溃和2007-2009年大衰退之后,金融市场宏观联系已成为货币政策建模中的一个重要问题。我们开发了一个动态模型,该模型包含非线性菲利普斯曲线、动态产出方程和非线性信贷流量方程——捕捉信贷周期、风险溢价和信贷利差的重要性。我们的非线性二次模型(NLQ)模型有三个动态状态方程和一个二次目标函数。它可以用来评估央行对大衰退从传统货币政策转向非常规货币政策的反应。我们使用欧元区的估计参数,用一种新的数值方法求解该模型。我们进行了模拟,以探索模型中非线性的(去)稳定效应。我们证明,信贷流量、风险溢价和信贷利差作为一种放大机制,在影响货币政策传导方面发挥着重要作用。因此,我们强调了自然利率作为央行目标锚的重要性,以及它对非常规货币政策有效性的信贷流动的重视。与许多央行采用的更大规模宏观经济计量模型相比,我们的模型在结构上相似。
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来源期刊
CiteScore
1.40
自引率
12.50%
发文量
34
期刊介绍: Studies in Nonlinear Dynamics & Econometrics (SNDE) recognizes that advances in statistics and dynamical systems theory may increase our understanding of economic and financial markets. The journal seeks both theoretical and applied papers that characterize and motivate nonlinear phenomena. Researchers are required to assist replication of empirical results by providing copies of data and programs online. Algorithms and rapid communications are also published.
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